Signaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about intermolecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be implemented on commercial confocal microscopes, allowing the investigation of interactions between multiple protein species at the plasma membrane. We demonstrate that SFSCS enables cross-talk-free cross-correlation, diffusion, and oligomerization analysis of up to four protein species labeled with strongly overlapping fluorophores. As an example, we investigate the interactions of influenza A virus (IAV) matrix protein 2 with two cellular host factors simultaneously. We furthermore apply raster spectral image correlation spectroscopy for the simultaneous analysis of up to four species and determine the stoichiometry of ternary IAV polymerase complexes in the cell nucleus. Living cells rely on transport and interaction of biomolecules to perform their diverse functions. To investigate the underlying molecular processes in the native cellular environment, minimally invasive techniques are needed. Fluorescence fluctuation spectroscopy (FFS) approaches provide a powerful toolbox that fulfills this aim . FFS takFFS studies are conventionally limited to the analysis of two spectrally distinguished species due to (i) broad emission spectra of fluorophores with consequent cross-talk artifacts and (ii) limited overlap of detection/excitation geometries for labels with large spectral separation. Generally, only a few fluorescence-based methods are available to detect ternary or higher order interactions of proteins . First iHere, we explore the full potential of FSCS and RSICS. In particular, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), combining SFCS and FSCS. We show that SFSCS enables cross-talk-free SFCCS measurements of two protein species at the PM of living cells tagged with strongly overlapping fluorophores in the green or red regions of the visible spectrum, excited with a single excitation line. This approach results in correct estimates of protein diffusion dynamics, oligomerization, and interactions between both species. Further, we extend our approach to the analysis of three or four interacting partners: by performing cross-correlation measurements on different fluorescent protein (FP) hetero-oligomers, we demonstrate that up to four FP species can be simultaneously analyzed. We then apply this scheme to simultaneously investigate the interaction of influenza A virus (IAV) matrix protein 2 (M2) with two cellular host factors, the tetraspanin CD9 and the autophagosome protein LC3, co-expressed in the same cell. Finally, we extend RSICS for the detection of four molecular species and quantify, for the first time directly in living cells, the complete stoichiometry of ternary IAV polymerase complexes assembling in the nucleus, using three-species fluorescence correlation and brightness analysis.To test the suitability of SFSCS to quantify interactions between membrane proteins tagged with strongly spectrally overlapping fluorophores, we investigated HEK 293T cells co-expressing myristoylated and palmitoylated mEGFP (mp-mEGFP) and mp-mEYFP. These monomeric FPs are anchored independently to the inner leaflet of the PM and their emission maxima are only ca. 20 nm apart . The sigOverlapping fluorescence emission from different species detected in the same channels provides unwanted background signal and thus reduces the signal-to-noise ratio (SNR) of the CFs . To asseNext, we tested whether the same approach can be used for FPs with overlapping emission in the red region of the visible spectrum, which generally suffer from reduced SNR in FFS applications . TherefoWe furthermore verified that SFSCS analysis results in correct estimates of protein diffusion dynamics. To this aim, we co-expressed mEGFP-tagged IAV hemagglutinin spike transmembrane protein (HA-mEGFP) and mp-mEYFP. We then compared the diffusion times measured by SFSCS to the values obtained on cells expressing each of the two constructs separately . For HA-fp) of ca. 60–75% for mEGFP  or mCherry2 and mEYFP .As a first step, we performed three-species SFSCS measurements on HEK 293T cells co-expressing mp-mEYFP with either (i) mp-mEGFP and mp-mCherry2 (mp-G+ mp-Y+ mp-Ch2) or (ii) mp-mCherry2-mEGFP heterodimers (mp-Ch2-G + mp-Y). Additionally, we tested a sample with cells expressing mp-mEYFP-mCherry2-mEGFP heterotrimers (mp-Y-Ch2-G). We then calculated ACFs for all three FP species and CCFs for all fluorophore combinations, respectively. In the first sample (mp-G + mp-Y + mp-Ch2), in which all three FPs are anchored independently to the PM, we obtained CCFs fluctuating around zero for all fluorophore combinations, as expected . In the fp of ca. 70% for mEGFP, as expected  to the values measured on cells co-expressing the three monomeric constructs mp-mEGFP, mp-mEYFP, and mp-mCherry2 (mp-G + mp-Y + mp-Ch2). Whereas similar brightness values were obtained for mEYFP and mCherry2 in both samples, for example, relative brightness of 1.04 ± 0.23 for mEYFP and 1.03 ± 0.21 for mCherry2 , a higher brightness of 1.70 ± 0.46 was measured for mEGFP in the first sample . This vaexpected . To confexpected , resultiHaving demonstrated the capability of SFSCS to successfully quantify protein interactions and oligomerization, even in the case of three FPs with overlapping emission spectra, we applied this approach in a biologically relevant context. In more detail, we investigated the interaction of IAV channel protein M2 with the cellular host factors CD9 and LC3. CD9 belongs to the family of tetraspanins and is supposedly involved in virus entry and virion assembly . The autCD9-G,LC3-Y = 0.09 ± 0.13, rel.cc.CD9-G,M2-Ch2 = 0.07 ± 0.09, mean ± SD, n = 19 cells) were similar to those of the negative cross-correlation control . In contrast, we detected a substantial rel.cc. of 0.52 ± 0.14 for LC3-mEYFP and M2-mCherry2. This value was close (ca. 90% on average) to that obtained for this fluorophore combination in measurements on FP heterotrimers, suggesting very strong association of LC3-mEYFP with M2-mCherry2. We furthermore analyzed the molecular brightness for each species, normalized to the monomeric references , suggesting that both proteins are monomers, we observed significantly higher relative brightness values for M2-mCherry2 (BM2-Ch2 = 2.24 ± 0.49). Assuming a fp of ca. 60% for mCherry2 . For the second sample (Ch2-G + Y-A), values significantly above zero, that is, rel.cc.G,Ch2 = 0.46 ± 0.09  and rel.cc.Y,A = 0.30±0.10, were only observed for two fluorophore pairs. For the third sample, cells expressing mEYFP-mCherry2-mEGFP-mApple hetero-tetramers (Y-Ch2-G-A), rel.cc. values significantly above zero were obtained for all FP pairs, ranging from rel.cc.A,Ch2 = 0.31 ± 0.11  to rel.cc.G,Y = 0.60 ± 0.05. Notably, rel.cc. values obtained for the FP species correlating in the second sample (Ch2-G + Y-A) were similar for the third sample (Y-Ch2-G-A): for example, rel.cc.G,Ch2 = 0.45 ± 0.07 and rel.cc.Y,A = 0.41 ± 0.06. The lower rel.cc. value measured for mEYFP and mApple in heterodimers (Ch2-G + Y-A) could be attributed to different linker sequences (long rigid linker in heterodimers vs. mCherry2-mEGFP and three long rigid linkers as spacer in hetero-tetramers [Y-Ch2-G-A]), possibly affecting FRET between neighboring FPs.From the amplitude ratios of ACFs and CCFs, we determined rel.cc. values . This anG = 19.4 ± 3.4 µm2/s and DCh2 = 20 ± 11 µm2/s  for mEGFP-mCherry2 heterodimers, and DG = 11.2 ± 2.5 µm2/s, DY = 11.6 ± 2.6 µm2/s, DA = 12.8 ± 3.2 µm2/s, DCh2 = 12.6 ± 5.0 µm2/s  for hetero-tetramers.Finally, we analyzed the diffusion dynamics of FP fusion proteins as determined from the spatial dependence of the ACFs for the four fluorophore species. Diffusion coefficients (D) obtained for mCherry2 showed the highest variation , reflectTo test the versatility of three-species RSICS, we quantified intracellular protein interactions and stoichiometries in a biologically relevant context. As an example, we focused on the assembly of the IAV polymerase complex (PC), consisting of the three subunits polymerase acidic protein (PA), polymerase basic protein 1 (PB1), and 2 (PB2). A previous investigation using FCCS suggested an assembly model in which PA and PB1 form heterodimers in the cytoplasm of cells. These are imported into the nucleus and appear to interact with PB2 to form heterotrimeric complexes . NeverthPB1-G,PA-Y = 0.93 ± 0.18 , rel.cc.PB1-G,PB2-Ch2 = 0.47 ± 0.14, rel.cc.PA-Y,PB2-Ch2 = 0.39 ± 0.14. For the positive control, similar values were observed for mEGFP and mCherry2, rel.cc.G,Ch2 = 0.48 ± 0.11 , whereas the values were higher than that measured for PCs for mEYFP and mCherry2, rel.cc.Y,Ch2 = 0.53 ± 0.11, and lower for mEGFP and mEYFP, rel.cc.G,Y = 0.65 ± 0.10. The lower average rel.cc. between PA-mEYFP and PB2-mCherry2 compared to the positive control indicates the presence of a minor fraction of non-interacting PA and PB2. These proteins could be present in the nucleus in unbound form when expressed in higher amount than PB1 since both PA and PB2 localize in the nucleus individually and were previously shown not to interact when both present without PB1  for mEGFP, mEYFP, and mCherry2, respectively, fp corrected normalized brightness values of εPB1-G = 2.1 ± 0.7 , εPA-Y = 1.8 ± 0.6, and εPB2-Ch2 = 2.2 ± 0.7 were obtained . These results suggest a 2:2:2 stoichiometry of the IAV PC subunits. Finally, we analyzed the diffusion dynamics of PCs via RSICS , was ca. 30% lower than the diffusion coefficients determined for PA-mEYFP- and PB2-mCherry2 (DPA-Y = 2.5 ± 0.9 µm2/s and DPB2-Ch2 = 2.6 ± 0.7 µm2/s). This observation is compatible with the above-mentioned presence of a minor fraction of unbound (and thus faster diffusing) PA and PB2 (likely in cells with a lower amount of PB1). A more detailed analysis of the data confirmed this interpretation: the molecular brightness and diffusion coefficient of PA-mEYFP depended on the relative concentration of PB1-mEGFP and PA-mEYFP. Lower brightness and higher diffusion coefficients were obtained in cells where PA-mEYFP was present at much higher concentrations than PB1-mEGFP  2x-mEGFP homodimers with mEYFP and mCherry monomers (2x-G + 1x-Y + 1x-Ch2) or (ii) the three homodimers 2x-mEGFP, 2x-mEYFP, and 2x-mCherry2 (2x-G + 2x-Y + 2x-Ch2). In the first sample, we observed an increased relative brightness of 1.67 ± 0.38  for mEGFP, whereas values around 1 were obtained for mEYFP and mCherry2. This confirmed the presence of mEGFP dimers as well as mEYFP and mCherry2 monomers in this control sample, as expected . In the f 60–75% . Next, wia RSICS . The aveB1-mEGFP .fp of 0.7 for each FP species and estimating the reduction due to imperfect overlap from the pair-wise rel.cc. values detected on the positive cross-correlation control . For a 2:2:2 stoichiometry, we obtained an estimated rel.3C. of 0.48, that is, only slightly higher than the average value determined experimentally for IAV PCs. Thus, we estimate that around 90% of PC subunits undergo ternary complex formation in the cell nucleus when all subunits are present.To directly confirm that IAV PC subunits form ternary complexes in the cell nucleus, we implemented a triple-correlation analysis (TRICS) to detect coincident fluctuations of the signal emitted by mEGFP-, mEYFP-, and mCherry2-tagged proteins. A similar analysis has previously been presented for three-channel FCS measurements  or red  part of the visible spectrum, we finally implemented three- and four-species SFSCS as well as four-species RSICS. These extensions do not further compromise the SNR of CFs detected for mEGFP and mEYFP see , but mayConventional two-color scanning FCCS has been previously applied to quantify receptor-ligand interactions in living zebrafish embryos  and CRISAs a first biological application of SFSCS, we investigated the interaction of IAV matrix protein M2 with two cellular host factors: the tetraspanin CD9 and the autophagosome protein LC3. We observed strong association of LC3 with M2, and consequent recruitment of LC3 to the PM , in agreFinally, we demonstrated that RSICS allows the quantification of the stoichiometry of higher order molecular complexes, based on molecular brightness analysis for each FP species. As example of an application in a biological context, we determined the stoichiometry of the IAV PC. Our data provide strong evidence for a 2:2:2 stoichiometry of the PC subunits PA, PB1, and PB2, that is, dimerization of heterotrimeric PCs. Such interactions were previously proposed based on experiments in solution using X-ray crystallography and cryo-electron microscopy , co-immuOf note, the RSICS approach presented here provides for the first time simultaneous information on molecular interactions, molecular brightness (and thus stoichiometry), diffusion dynamics, and concentration for all three complex subunits. This specific feature opens the possibility of a more in-depth analysis. For example, it is possible to quantify the relative cross-correlation of two subunits, e.g. PA and PB2, as a function of the relative concentration of the third subunit, for example, PB1 . SimilarWe summarize in this section the main instrumental, conceptual, and sample-related limitations and requirements connected to the multicolor FFS approach employed in this work.To perform multicolor FFS, a spectral photon counting detector system is required. Alternatively, the same conceptual approach can be implemented based on detection of fluorophore lifetimes rather than emission spectra . For botFFS approaches generally require the proteins of interest to diffuse and thus cannot be applied in the case of immobile or strongly clustered targets . The staTo apply multicolor FFS, multiple FP species  have to be expressed in the same cell, in relative amounts compatible with the ranges given above. Since tagging of proteins of interest with FPs is required , potential hindrance of protein interactions by the tags should be carefully evaluated. Typical measures consist in, for example, testing different positions for the tag in the protein of interest, trying different linkers with varying length and flexibility, using tags with smaller sizes, or bio-orthogonal labeling . The emiIn summary, we present here three-species and, for the first time, four-species measurements of protein interactions and diffusion dynamics in living cells. This is achieved by combining and extending existing FFS techniques with spectrally resolved detection. The presented approaches provide a powerful toolbox to investigate complex protein interaction networks in living cells and organisms.Human embryonic kidney (HEK) cells from the 293T line  and human epithelial lung cells A549  were cultured in Dulbecco’s modified Eagle medium (DMEM) with the addition of fetal bovine serum (10%), L-glutamine (2 mM), penicillin (100 U/mL), and streptomycin (100 µg/mL). Mycoplasma contamination tests and morphology tests were performed every 3 months and 2 weeks, respectively. Cells were passaged every 3–5 days, no more than 15 times. All solutions, buffers, and media used for cell culture were purchased from PAN-Biotech .5 (HEK) or 4 × 105 (A549) cells were seeded in 35 mm #1.5 optical glass-bottom dishes  24 hr before transfection. Cells were transfected 16–24 hr prior to the experiment using between 50 ng and 150 ng plasmid per dish with Turbofect (HEK) or Lipofectamin3000 (A549) according to the manufacturer’s instructions . Briefly, plasmids were incubated for 20 min with 3 μl Turbofect diluted in 50 μl serum-free medium, or 15 min with 2 μl P3000 and 2 μl Lipofectamine3000 diluted in 100 μl serum-free medium, and then added dropwise to the cells. For spectral imaging at different pH values, culture medium was exchanged with buffer containing 140 mM NaCl, 2.5 mM KCl, 1.8 mM CaCl2, 1.0 mM MgCl2, and 20 mM HEPES with pH ranging from 5.0 to 9.2.For microscopy experiments, 3 × 10The plasmids encoding FPs linked to a myristoylated and palmitoylated peptide , the full-length IAV A/chicken/FPV/Rostock/1934 hemagglutinin (HA) construct HA-mEGFP, and the plasmids for cytosolic expression of mEGFP, mEYFP, mCherry2, 2x-mEGFP, 2x-mEYFP, 2x-mCherry2, and mCherry2-mEGFP heterodimers were previously described  and are For the cloning of all following constructs, standard PCRs with custom-designed primers were performed, followed by digestion with fast digest restriction enzymes and ligation with T4-DNA-Ligase according to the manufacturer’s instructions. All enzymes and reagents were purchased from Thermo Fisher Scientific.To obtain mp-mEGFP-mEYFP, a mp-mEGFP_pcDNA3.1+ vector was first generated by amplifying mp-mEGFP insert from the respective plasmid, and inserting it into pcDNA3.1+ vector (obtained from Thermo Fisher Scientific) by digestion with NheI and AflII. Afterwards, mEYFP was amplified from mp-mEYFP and inserted into mp-mEGFP_pcDNA3.1+ using digestion with AflII and KpnI. To clone mp-mEYFP-(L)-mEGFP (a plasmid encoding for mp-mEYFP-mEGFP heterodimers with a long rigid linker peptide [L] between FPs), a mp-mEYFP-(L)_pcDNA3.1+ construct was first generated by amplifying mp-mEYFP from the respective plasmid with primers encoding for the rigid linker see   and inserting into mEGFP-C1 vector using restriction by HindIII and BamHI. The LC3-mEYFP plasmid was generated by inserting mEYFP from mEYFP-C1 vector into pmRFP-LC3   using a 40×, 1.2 NA water immersion objective. For two-species measurements, samples were excited with a 488 nm argon laser  or a 561 nm diode laser . For three- and four-species measurements, both laser lines were used. To split excitation and emission light, 488 nm (for two-species measurements with mEGFP and mEYFP) or 488/561 nm (for measurements including mCherry2 and mApple) dichroic mirrors were used. Fluorescence was detected in spectral channels of 8.9 nm  on a 32-channel GaAsP array detector operating in photon counting mode. All measurements were performed at room temperature.For SFSCS measurements, line scans of 256 × 1 pixels (pixel size 80 nm) was performed perpendicular to the PM with 403.20 µs scan time. This time resolution is sufficient to reliably detect the diffusion dynamics observed in the samples described in this work . Typically, 450,000–600,000 lines were acquired . Laser powers were adjusted to keep photobleaching below 50% at maximum for all species . Typical excitation powers were ca. 5.6 µW (488 nm) and ca. 5.9 µW (561 nm). Spectral scanning data were exported as TIFF files , imported, and analyzed in MATLAB  using custom-written code .SFSCS analysis followed the scanning FCS scheme described previously , combineSpectral filter functions D is a diagonal matrix, Here, In order to correct for depletion due to photobleaching, a two-component exponential function was fitted to the fluorescence time series for each spectral species,  applied . Finallywhere To avoid artifacts caused by long-term instabilities or single bright events, CFs were calculated segment-wise (10–20 segments) and then averaged. Segments showing clear distortions  were manually removed from the analysis .A model for two-dimensional diffusion in the membrane and Gaussian focal volume geometry  was fittN and thus To ensure convergence of the fit for all samples , positive initial fit values for the particle number  CFs see .S was fixed to the average value determined in calibration measurements .To calibrate the focal volume, point FCS measurements with Alexa Fluor 488 (Thermo Fisher Scientific) dissolved in water at 20 nM were performed at the same laser power. The structure parameter From the amplitudes of ACFs and CCFs, rel.cc. values were calculated for all cross-correlation combinations:i,jG(0) is the amplitude of the CCF of species i and j, and iG(0) the amplitude of the ACF of species i. The molecular brightness was calculated by dividing the mean count rate detected for each species i by the particle number iN determined from the fit: iB by the average molecular brightness i,1B of the corresponding monomeric reference, and, subsequently, by the fluorescence probability f,ip for species i: fp was previously characterized for several FPs  (where  derived . The pf Cherry2) .The SNR of the ACFs was calculated by dividing ACF values by their variance and summing over all points of the ACF. The variance of each point of the ACF was calculated in the multiple tau algorithm .To ensure statistical robustness of the SFSCS analysis and sufficient SNR, the analysis was restricted to cells expressing all fluorophore species in comparable amounts, that is, relative average signal intensities of less than 1:10 (mEGFP/mEYFP) or 1:5 .2 through the midplane of cells), 2.05 µs or 4.10 µs pixel dwell time, 1.23 ms or 2.46 ms line, and 314.57 ms or 629.14 ms frame time . Samples were excited at ca. 5.6 µW (488 nm) and 4.6 µW (561 nm) excitation powers, respectively. Laser powers were chosen to maximize the signal emitted by each fluorophore species but keeping photobleaching below 50% at maximum for all species . Typical counts per molecule were ca. 25 kHz for mEGFP (G), 15–20 kHz for mEYFP (Y), 20–30 kHz for mApple (A), and 5–10 kHz for mCherry2 (Ch2). To obtain reference emission spectra for each individual fluorophore species, four image stacks of 25 frames were acquired at the same imaging settings on single-species samples on each day.RSICS measurements were performed as previously described . Brieflyk spectral channels) were imported in MATLAB (The MathWorks) from CZI image files using the Bioformats package , respectively where N, diffusion coefficient D, waist S as free fit parameters) was then fitted to both ACFs and CCFs:ACF amplitudes were corrected as described in where From the fit amplitudes of the ACFs and CCFs, rel.cc. values were calculated:i,jG is the amplitude of the CCF of species i and j, and iG the ACF amplitude of species i. In the case of non-meaningful convergence of the fit to the CCFs . From the resulting four-dimensional matrix, a two-dimensional representation was calculated by introducing coordinates a, b for the effective spatial shift between signal fluctuations evaluated for the two-species combinations:where 3C by rounding up a and b to integer values and averaging all points with the same rounded spatial shift. For example, for a one-pixel shift along a line in one FP channel and a one-pixel shift along a column in the third FP channel  also includes in its averaged value the other seven correlation values corresponding, for example, to  includes and averages only the two correlation values corresponding to a = 2 and b = 0, but these values were not included since they refer to a correlation between identical pixel positions , the closest points , 3CG, 3CG, 3CG3C) of the two-dimensional triple correlation were averaged as an (slightly underestimated) approximation of the amplitude value at . Note that we chose not to include 3C because this point is the average of only two possible spatial shift combinations, resulting in large statistical noise. Also, the point 3C was not included since it refers to shifts along columns , which, in turn, are characterized by a steeper decrease in amplitude. Finally, for best visualization, 3CG is plotted for a and b values ≥ 1  and p-values are given in figure captions. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:This manuscript provides a new tool to study multi-protein interaction in living cells based on fluorescence fluctuation spectroscopy. The paper includes a reliable validation and description of the method as well as a proof of principle application and assessment of potential limitations.Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewers, and the evaluation has been overseen by Anna Akhmanova as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Erdinc Sezgin (Reviewer #2); Thorsten Wohland (Reviewer #3).Thank you for submitting your article "Multi-color fluorescence fluctuation spectroscopy in living cells via spectral detection" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:The manuscript is well written and the data very diligently analysed. There remain mainly technical questions and some points that should be discussed to ensure consistency of the results.1. Figure 1: It seems like the time resolution of the measurements are on the order of several milliseconds. But the diffusion time measured are on the order of ~9 ms. With the time resolution relatively close to the measured diffusion time, did the authors check whether diffusion times are biased?2. Page 11: Why are correlation amplitudes limited to positive values? The authors mention this also in the supplement but don't explain why that is necessary. For true correlations, only positive values should be obtained. And I assume that is so in their case, if not that should be addressed. Any negative values would be a clear indication that the correlation just indicates noise. This could also be compared with the actual correlation times measured. For correlations of noise, it is not only the amplitude that varies strongly but also the correlation times typically vary widely and mostly do no coincide with expected or reasonable values. The authors might be able to use that criterion to identify non-correlated data and thus avoid the positive amplitudes which are artifacts of the restrictions of the fitting parameters.3. Page 11 and 12: It would be interesting if the authors could determine whether the observed correlation amplitudes are consistent with the probability of the different FPs . If FRET influences these amplitudes, the authors might be even able to extract FRET efficiencies and demonstrate FRET. Another possibility would be to measure fluorescence lifetimes to determine FRET?4. Page 19/20: The diffusion coefficient for the hetero-tetramer is only about half of the one determined for hetero-dimers. As these are membrane probes with the fluorescent proteins not expected to interact with the membrane, is there an explanation for the factor 2?5. Did the authors determine the various observation volumes, given the concentrations they measure and the probability of fluorescence of the fluorescent proteins they determined? And is this consistent with the difference in diffusion coefficient they see for the hetero-oligomers?6. Page 22: The authors indicate that they normalize their RSICS brightness data to measurements of monomers on the same day. It would be interesting if the authors could comment on the day-to-day variability of their calibrations.7. Figure 3. M2 protein oligomerize but its interacting partner LC3 does not, does that mean each single LC3 associates with multiple M2 protein? Can authors confirm this by looking at the diffusion coefficients from the FCs curves?8. The authors provided a validation of the method in HEK cells expressing the three Fluorescent Proteins in the plasma membrane in different oligomerization states . I'm wondering how relatively changes in concentration/expression i.e. fluctuations within the 3 species of probes would influence the observable. Several applications might aim to study interaction within proteins of different abundance, it is important to understand the relative concentration range where the method can be used and provide reliable results. I suggest the authors to provide further experiment and eventually simulation to characterize such dynamic range.9. The authors applied SFSCS to study how the Influenza A virus matrix protein 2 interact with the autophagy protein LC3 and the tetraspanin CD9. They found that IAV preferentially interact LC3 but not with CD9 . How the position of the label influences the cross-correlation studies?10. For this technique to be applicable by other researchers, the data analysis tool should be openly available to others. Can authors put their software in an open repository?11. Since it is a new technique all the limitations of the technique can be discussed in a "limitations" subsection. That would give the readers a clear picture what can and cannot be done with this new technique.Reviewer #1 (Recommendations for the authors):Multiplexing methods focusing on dynamic studies are challenging yet very important to understand cellular mechanism at the molecular level. Usually such studies are complex and done on specialized system, this work presents a method easily translatable to commercial system and compatible with standard fluorophores with a well-described analysis pipeline.Therefore, it can open up several new dynamic studies with 3-4 fluorophores simultaneous read-out.The choice of fluorophores, its dimerization tendency and the relative labeling densities of each species might influence the cross-correlation observable so a careful validation should be considered and discussed to validate the general applicability of the methodology in various biological applications.To the author:1 – The authors provided a validation of the method in HEK cells expressing the three Fluorescent Proteins in the plasma membrane in different oligomerization sates . I'm wondering how relatively changes in concentration/expression i.e. fluctuations within the 3 species of probes would influence the observable. Several applications might aim to study interaction within proteins of different abundance, it is important to understand the relative concentration range where the method can be used and provide reliable results. I suggest the authors to provide further experiment and eventually simulation to characterize such dynamic range.2 –The authors applied SFSCS to study how the Influenza A virus matrix protein 2 interact with the autophagy protein LC3 and the tetraspanin CD9. They found that IAV preferentially interact LC3 but not with CD9 . How the position of the label influences the cross-correlation studies?Reviewer #2 (Recommendations for the authors):In this paper, the authors developed a new modality of multi-color FCS using spectral detection to investigate stoichiometry of multi-component complexes in live cells. They showed the proof-of-principle with tandem proteins. Furthermore, they showed the biological application of their methodology by investigating Influenza virus components. This will be a useful addition to live cell spectroscopy tools to study protein-protein interactions. The authors' claims are supported by the data throughput the manuscript. The data is analyzed carefully, and results were reported clearly. This method is likely to be used by cell biologists to determine the stoichiometry of multi-protein complexes.– Figure 3. M2 protein oligomerize but its interacting partner LC3 does not, does that mean each single LC3 associates with multiple M2 protein? Can authors confirm this by looking at the diffusion coefficients from the FCs curves?– For this technique to be applicable by other researchers, the data analysis tool should be openly available to others. Can authors put their software in an open repository?– Since it is a new technique all the limitations of the technique can be discussed in a "limitations" subsection. That would give the readers a clear picture what can and cannot be done with this new technique.Reviewer #3 (Recommendations for the authors):This manuscript is a carefully conducted study of multi-color fluorescence fluctuation spectroscopy as applied to plasma membranes. By using two-wavelength excitation and spectral detection in a scanning mode the authors show that they can determine the cross-correlation between up to four different probes in a single measurement. In addition, they build on their earlier work and show that the collected data can be analysed by Number and Brightness analysis, providing access to biomolecular stoichiometry. The authors use a range of protein constructs that include between one to four fluorescent proteins, which they use in different compositions to demonstrate that they can analyse all possible interactions of four probes in a single measurement. They then apply the technique to the interaction of influenza A proteins. They show that the influenza A virus (IAV) matrix protein 2 (M2) interacts more strongly with LC3 compared to CD9, both host cell factors. As they measure multiple probes simultaneously, the authors can go beyond binary correlations. Using triple correlations the authors show that they can detect the interaction of the proteins PA, PB1, and PB2 of the IAV polymerase complex. The extension of FCS to four probes, the demonstration of triple correlations and the application to a biological context provides important progress in fluorescence fluctuation spectroscopy and will allow the measurements of complex interactions at the cellular membranes.The manuscript is well written and the data very diligently analysed. There remain mainly technical questions and some points that should be discussed to ensure consistency of the results.1. Figure 1: It seems like the time resolution of the measurements are on the order of several milliseconds. But the diffusion time measured are on the order of ~9 ms. With the time resolution relatively close to the measured diffusion time, did the authors check whether diffusion times are biased?2. Page 11: Why are correlation amplitudes limited to positive values? The authors mention this also in the supplement but don't explain why that is necessary. For true correlations, only positive values should be obtained. And I assume that is so in their case, if not that should be addressed. Any negative values would be a clear indication that the correlation just indicates noise. This could also be compared with the actual correlation times measured. For correlations of noise, it is not only the amplitude that varies strongly but also the correlation times typically vary widely and mostly do no coincide with expected or reasonable values. The authors might be able to use that criterion to identify non-correlated data and thus avoid the positive amplitudes whioch are artefacts of the restrictions of the fitting parameters.3. Page 11 and 12: It would be interesting if the authors could determine whether the observed correlation amplitudes are consistent with the probability of the different FPs . If FRET influences these amplitudes, the authors might be even able to extract FRET efficiencies and demonstrate FRET. Another possibility would be to measure fluorescence lifetimes to determine FRET?4. Page 19/20: The diffusion coefficient for the hetero-tetramer is only about half of the one determined for hetero-dimers. As these are membrane probes with the fluorescent proteins not expected to interact with the membrane, is there an explanation for the factor 2?5. Did the authors determine the various observation volumes, given the concentrations they measure and the probability of fluorescence of the fluorescent proteins they determined? And is this consistent with the difference in diffusion coefficient they see for the hetero-oligomers?6. Page 22: The authors indicate that they normalize their RSICS brightness data to measurements of monomers on the same day. It would be interesting if the authors could comment on the day-to-day variability of their calibrations. Essential revisions:The manuscript is well written and the data very diligently analysed. There remain mainly technical questions and some points that should be discussed to ensure consistency of the results.1. Figure 1: It seems like the time resolution of the measurements are on the order of several milliseconds. But the diffusion time measured are on the order of ~9 ms. With the time resolution relatively close to the measured diffusion time, did the authors check whether diffusion times are biased?The time resolution of the SFSCS measurements was ca. 0.8 ms, since the line-scan time was ca. 0.4 ms and a 2-line binning was performed. To assess whether this time resolution is sufficient to detect the diffusion dynamics observed in the experiments, we re-analyzed a three-species SFSCS measurement acquired on cells co-expressing membrane-anchored FPs (mp-1x-G + mp-1x-Y + mp-1x-Ch2) using a variable time binning . We have now clarified these passages . Briefly, the presence of positive correlation values in noisy curves is a consequence of positive starting parameters for the fit routine and, probably, its converging to a local minimum .The  reason for consistently using positive starting values for the correlation was that in the case of clear interactions (e.g. cross-correlation for the positive controls), only positive initial amplitude values resulted in robust and reproducible fitting of the CCF. Negative initial values resulted in errors in the fit routine or fit curves that clearly did not provide a reliable fit to the CFs. To perform an unbiased analysis, the same (positive) initial values were thus used for all samples, sometimes resulting in low “false-positive” amplitudes in the absence of interactions for noisy curves. This in now stated in lines 1024-1029.We agree with the reviewer that, for the case of pure noise, a symmetric distribution of fit amplitudes around 0 is expected. We have thus implemented an alternative fit routine, which calculates the starting parameter for the amplitude as the average of the first 5 points of each CF. In the case of pure noise, this results in positive or negative fit amplitudes, as mentioned by the reviewer. In the case of interactions, the fit converges to positive values. To evaluate this fit routine, we have reanalyzed a set of three-species SFSCS measurements on cells co-expressing mp-mCherry2-mEGFP hetero-dimers and mp-mEYFP. The new fit procedure , some likely false-positive correlation is removed . If FRET influences these amplitudes, the authors might be even able to extract FRET efficiencies and demonstrate FRET. Another possibility would be to measure fluorescence lifetimes to determine FRET?f to be fluorescent, the expected rel.cc. is equal to pf, as we discuss in the Appendix of the paper (Appendix-table 1). Since all FPs  exhibit similar pf of ≈70%, the expected rel.cc. is ≈0.7 for all FP pairs. The values obtained for cross-correlation of mEGFP and mEYFP signals (with a rigid linker) are indeed close to the expected value . A significantly lower rel.cc. of 0.60 was obtained with a short linker peptide between the two FPs, suggesting the presence of FRET . For the other FP combinations requiring excitation with two laser lines, the obtained rel.cc. values are lower than expected (e.g. rel.cc.=0.56 and 0.57 for mEGFP/mCherry2 and mEYFP/mCherry2 in heterotrimers). In addition to non-fluorescent states, differences in observation volumes and FRET can reduce the experimentally observed rel.cc., as pointed out by the reviewer. We address the issue of imperfect overlap below, in the response to question 5. To minimize FRET artifacts, FPs in hetero-trimers and tetramers were linked by a rigid linker. Nevertheless, residual FRET may still occur. To assess FRET between FPs, we quantified the molecular brightness of FPs coupled in hetero-oligomers and compared it with the brightness obtained on the same FPs expressed as independent monomers. The brightness ratios qi  are shown below for SFSCS measurements on cells expressing mp-mEYFP-mCherry2-mEGFP hetero-trimers (E) are related to the decrease in donor brightness, fE=1-qG . We observed a systematic reduction of the brightness of mEGFP, no , for hetero-dimers and hetero-trimers respectively. Thus, FRET has a minor effect (<10%) on the cross-correlation and alone cannot explain the reduced rel.cc. observed for pairs of green/yellow and red FPs. It should be noted that, in the case of hetero-trimers, our analysis based on the effective molecular brightness is a simplified approximation, since all three FP pairs may undergo FRET to different extent. We agree with the reviewer that it is important to keep FRET into consideration when planning experiments and constructs, in particular because hetero-oligomers are commonly used as a positive control to normalize the rel.cc. obtained on proteins of interest. We have therefore added a comment on FRET to the Limitations section (lines 864-869).For FPs with a probability p-trimers  or coexp-trimers . FRET efEGFP, no  or small4. Page 19/20: The diffusion coefficient for the hetero-tetramer is only about half of the one determined for hetero-dimers. As these are membrane probes with the fluorescent proteins not expected to interact with the membrane, is there an explanation for the factor 2?We think that this comment might arise from a misunderstanding. The data shown on Page 19/20 were obtained by RSICS measurements in the cytoplasm, not on the plasma membrane. Thus, diffusion coefficients reasonably depend on oligomer size. The obtained values for the diffusion of FP oligomers, e.g. diffusion of FP tetramer about 2.5 times slower than diffusion of monomers, are in good agreement with previous studies . We have clarified this issue in lines 447 and 467.5. Did the authors determine the various observation volumes, given the concentrations they measure and the probability of fluorescence of the fluorescent proteins they determined? And is this consistent with the difference in diffusion coefficient they see for the hetero-oligomers?We have already taken imperfect overlap of the observation volumes into account for comparison of the experimental triple correlation with simulation results (see results and Appendix for triple correlation) but have not determined the size and potential displacement of observation volumes explicitly.f (e.g. lower pf corresponds to higher amplitude). For all FPs evaluated here, pf values are similar . Thus, if the observation volumes were the same, the relative amplitudes should be close to 1, as shown indeed in f are small. More precisely, one would expect a slightly larger observation volume for mCherry2 than for mEGFP (due to the higher wavelength) and thus an amplitude ratio GCh2/GG smaller than 1. However, values slightly larger than 1 are obtained. This might be due to e.g. slightly smaller pf of mCherry2. In addition, residual FRET (see point 3) may increase the ACF amplitude of the acceptor fluorophore, here mCherry2 .As mentioned in our response to point 3, differences in observation volumes for different FP channels may cause the lower than expected rel.cc. obtained for pairs of green/yellow and red FPs, e.g. mEGFP/mCherry2. To evaluate such differences, we have analyzed the relative ACF amplitudes and diffusion times obtained from SFSCS measurements on FP hetero-oligomers, i.e. mp-mEYFP-mCherry2-mEGFP hetero-trimers and mp-mEGFP-mCherry2 hetero-dimers in the different channels . As shown in eff=Π∙S∙w02. The results are shown in Ch2/taudG=1.35) indicates a ca. 35% difference in size and a slight shift of observation volumes . Calculating the effective overlapping observation area from the cross-correlation diffusion time , the determined FRET efficiencies  and keeping the pf values (0.7 for both) into account, we calculated an expected rel.cc. of ca. 0.50 for mp-mCherry2-mEGFP hetero-dimers, which is very close the experimental value of 0.45. Thus we conclude that the deviation from the expected rel.cc.  for FP combinations involving excitation by two laser lines in general might be caused by both, FRET, and imperfect overlap of the observation volumes.Due to the difficulties in interpreting the ACF amplitudes, we have therefore directly evaluated the diffusion times of mp-mCherry2-mEGFP hetero-dimers obtained from ACFs and from CCFs. In scanning FCS, the diffusion times scale with the effective observation area AWe have added the issue of imperfect overlap, which applies to SFSCS as to standard FCCS as soon as a second excitation line is used, to the limitations section (lines 824-826) and state it more clearly also in the discussion (lines 670-674). Therein, we stress the point that for two-species measurements, the fact that only one laser line is needed provides a clear advantage of the spectral approach, resulting in higher rel.cc. (up to 0.8).6. Page 22: The authors indicate that they normalize their RSICS brightness data to measurements of monomers on the same day. It would be interesting if the authors could comment on the day-to-day variability of their calibrations.We thank the reviewer for this comment and agree that data on day-to-day variability are highly useful and often underreported in brightness studies. We have examined both the day-to-day variability of the relative brightness values of the homo-dimer control and of the absolute brightness of the monomeric reference on the same day. The data has been added to the SI and refer to in the results (lines 591-592).7. Figure 3. M2 protein oligomerize but its interacting partner LC3 does not, does that mean each single LC3 associates with multiple M2 protein? Can authors confirm this by looking at the diffusion coefficients from the FCs curves?Yes, we think that LC3 monomers bind to M2 oligomers in (apparent) average stoichiometry of 1:2 to 1:4. In the discussion of the paper, we speculate already that LC3 does not show higher oligomerization (or higher stoichiometry in the binding to M2) because endogenous LC3 or other cellular proteins might block additional binding sites in M2 oligomers, or because of steric hindrance. We have evaluated the diffusion dynamics of M2 and LC3 see . Althoug8. The authors provided a validation of the method in HEK cells expressing the three Fluorescent Proteins in the plasma membrane in different oligomerization sates . I'm wondering how relatively changes in concentration/expression i.e. fluctuations within the 3 species of probes would influence the observable. Several applications might aim to study interaction within proteins of different abundance, it is important to understand the relatively concentration range where the method can be used and provide reliable results. I suggest the authors to provide further experiment and eventually simulation to characterize such dynamic range.We thank the reviewer for this comment and agree that the relative concentration range that provides reliable results is important to explore. We have therefore already carefully evaluated the SNR of two-species SFSCS measurements as a function of the relative concentrations (i.e. intensities), which we show in Figure 1. In addition, we have extensively discussed the allowed relative concentration range for 2-,3-, and 4-species measurements in the discussion and methods section of the paper (e.g. 1:5 for neighboring FP species in 4-species measurements), and have compared it to the limitations of similar approaches such as fluorescence lifetime correlation spectroscopy. In order to explicitly address the question for three-species SFSCS , we have now analyzed the SNR of the ACFs obtained from measurements on cells co-expressing mp-mEGFP, mp-mEYFP and mp-mCherry2 see . The SNRGiven that mEYFP is the most compromised of the three species, we have then evaluated the diffusion time and molecular brightness obtained for mEYFP in three groups corresponding to the highest, middle and lowest third of the 31 data points, sorted by SNR. The obtained results  are very9. The authors applied SFSCS to study how the Influenza A virus matrix protein 2 interact with the autophagy protein LC3 and the tetraspanin CD9. They found that IAV preferentially interact LC3 but not with CD9 . How the position of the label influences the cross-correlation studies?To minimize the influence of the fluorophore tags on our interaction study, we chose a reasonable labeling approach. The M2 protein was tagged at the extracellular N-terminus. Binding with LC3 occurs via an LIR-motif in the flexible cytoplasmic tail of M2 . LC3 docks with the LIR motif via hydrophobic pockets located in the middle region of its sequence . We placed the mEYFP tag at the C-terminus of LC3, i.e. at some distance from the binding region. Thus, we do not expect interference of the FP tags with M2-LC3 interactions.For CD9, both N- and C-terminus and intracellular. The mEGFP-tag is located at the C-terminus, with a 10aa linker. Having the tags on M2 and CD9 on different sides of the plasma membrane (EC/IC) should minimize potential hindrance in the interactions. Binding e.g. via the TMDs should not be affected. Given the flexibility of the cytoplasmic tail of M2, we do not think that the tag on CD9 hinders M2-CD9 interactions. Nevertheless, we cannot rule this out completely and thus added a sentence to the manuscript (lines 776-778). In addition, we have added a discussion on the general requirements of fluorophore tags and potential interference with protein-protein interactions to the Limitations section (lines 848-853).10. For this technique to be applicable by other researchers, the data analysis tool should be openly available to others. Can authors put their software in an open repository?We agree that it would be very beneficial to have the code openly available. We have therefore uploaded all analysis code  and a documentation to run the main scripts on GitHub .11. Since it is a new technique all the limitations of the technique can be discussed in a "limitations" subsection. That would give the readers a clear picture what can and cannot be done with this new technique.We thank the reviewer for this idea and have added a “Limitations” subsection at the end of the discussion, summarizing the main technical and conceptual limitations of the technique.


Increased values of IL-6, CRP, and HSP-70 represented an early inflammatory response to distal forearm fractures classified as SH-II type according to the Salter-Harris classification system. However, the median CRP concentration was within the reference values not indicative of inflammation. The CRKF procedure may be a good solution for the treatment of bone fractures, as damaged associated molecular patterns – HMGB-1 and HSP-70 – did not significantly differ 12-14 hours after the approach was applied as compared to the control group. Moreover, the increase in IL-6 concentration after the CRKF procedure was 1.5-fold to the level before CRKF, while the increase of this marker in response to the distal forearm fracture was 4.3-fold compared to the control group. Based on this data, it appears reasonable to suggest that the CRKF approach caused less damage and inflammatory response in comparison to the response to the fracture itself.The evaluation of trauma after surgery through objective analysis of biochemical markers can help in selecting the most appropriate therapy. Thus the aim of the study was the evaluation of the concentration of selected inflammatory cytokines , C-reactive protein (CRP), and damaged-associated molecular patterns (DAMPs): HMGB-1, HSP-70 in the plasma of children in response to bone fracture and 12-14 hours after subsequent surgery performed by closed reduction with percutaneous Kirschner wire fixation (CRKF). The study will answer the question if the CRFK procedure leads to excessive production of inflammatory and damage markers. Blood samples from 29 children with distal forearm fractures were collected 30 min. before CRKF procedure and 12-14 hours after performance of the procedure. The control group was composed of 17 healthy children. IL-6 and CRP concentrations were analyzed using routinely performed  Close Reduction and the distal radius percutaneous Kirschner wire Fixation (CRKF) have been advocated as a safe and reliable technique for maintaining the alignment of the fracture and avoiding re-displacement and further manipulation , C-reactive protein (CRP), and DAMPs  in the plasma of children in response to bone fracture and investigation into how the closed reduction with percutaneous Kirschner wire fixation (CRKF) affected the levels of these molecules 12-14 hours after the surgical procedure. The conducted study will answer the question if the CRFK procedure leads to excessive production of inflammatory and damage markers. Such comprehensive analysis has not been performed thus far.The study population comprised 29 skeletally immature children admitted between 2019-2020 to the Pediatric Orthopaedics and Traumatology Department of the Medical University of Bialystok due to distal forearm fracture, directed to CRKF procedure. All fractures resulted from falls from low-energy trauma, followed by injury at the playground or contact activities. The inclusion criteria were: distal forearm displace fractures involving the physis, skeletally immature children, female or male patients aged between 5-15, the CRKF lasting up to 60 min., and no comorbidities. Fracture displacement in the current study was defined when the angulation of the fracture was greater than 45° or when the fracture had less than 50% of bony contact or when there was a complete displacement of the fracture in the initial injury. In all patients, fractures were classified according to the Salter-Harris classification system as SH-II type . ExclusiThose children whose parents gave informed consent for both clinical and biochemical follow-up were included in the study.17 healthy children, aged-matched to the study group, whose parents gave informed consent for both clinical and biochemical follow-up, served as a control group.Approval for this study was obtained from the Local Bioethics Committee (Permission No: R-I-002/45/2018). Procedures were following the ethical standards set out in the Declaration of Helsinki put out by World Medical Association.® 1.2 ml K3E, SARSTEDT) 30 min., before closed reduction with percutaneous Kirschner wire fixation (pre-CRKF) and 12-14 hours after performance of the procedure (post-CRKF). After the centrifugation (20 min. at 1000 g force) plasma samples were aliquoted and stored at -80°C until further analysis.Blood samples from children with distal forearm fracture were collected into test tubes with EDTA-K (S-Monovettein vitro diagnostics electrochemiluminescence immunoassay (ECLIA) test on the COBAS e411 analyzer  from Roche Diagnostics, Penzberg, Germany, according to the manufacturer’s instructions. Plasma samples were not diluted before analysis. The detection range of the assay test is 1.5-5000 pg/ml. The manufacturer of the assay kit referred to the diagnostic repeatability coefficient of variation (CV%) as 2.9% at IL-6 mean concentration of 12.1 ± 0.346 pg/mL and diagnostic precision CV% as 3.1% at IL-6 mean concentration of 12.1 ± 0.371 pg/mL.IL-6 concentration was measured using an IL-33, IL-8, CXCL5, HSP70, and HMGB1 concentrations were analyzed using the ELISA (enzyme-linked immunosorbent assay) method in compliance with the manufacturer’s instructions. Plasma samples for IL-33, IL-8, HSP70, and HMGB1 concentration evaluation were not diluted before analysis. Plasma samples for CXCL5 concentration evaluation were diluted 2-fold before analysis.IL-33 concentration was measured using a Human IL-33 ELISA kit  from R&D Systems, Abingdon, UK. The detection range for the kit is between 3.13-200 pg/mL, the mean minimum detectable dose (sensitivity) of the assay is 0.357 pg/mL. The manufacturer of the assay kit referred to the intra-assay coefficient of variation (CV%) as 3.7% at IL-33 mean concentration of 31.0 ± 1.15 pg/mL and inter-assay CV% as 4.4% at IL-33 mean concentration of 31.0 ± 1.35 pg/mL. The average recovery of IL-33 concentration throughout the range of the assay for EDTA-K plasma is 91% (range 83-103%).CXCL5 concentration was measured using a Human CXCL5/ENA-78 ELISA kit  from R&D Systems, Abingdon, UK. The detection range for the kit is between 31.3-2000 pg/mL, the mean minimum detectable dose (sensitivity) of the assay is 15 pg/mL. The manufacturer of the assay kit referred to the intra-assay coefficient of variation (CV%) as 5.3% at CXCL5 mean concentration of 244 ± 12.9 pg/mL and inter-assay CV% as 7.4% at CXCL5 mean concentration of 240 ± 17.8 pg/mL. The average recovery of CXCL5 concentration throughout the range of the assay for EDTA-K plasma is 98% (range 92-104%).IL-8 concentration was measured using a Human IL-8/CXCL8 ELISA kit  from R&D Systems, Abingdon, UK. The detection range for the kit is between 31.3-2000 pg/mL, the mean minimum detectable dose (sensitivity) of the assay is 3.5 pg/mL. The manufacturer of the assay kit referred to the intra-assay coefficient of variation (CV%) as 5.6% at IL-8 mean concentration of 168 ± 9.4 pg/mL and inter-assay CV% as 7.4% at IL-8 mean concentration of 196 ± 14.5 pg/mL. The average recovery of IL-8 concentration throughout the range of the assay for EDTA-K plasma is 103% (range 97-111%).HSP70 concentration was evaluated using a Biorbyt Human heat shock proteins (HSP70) ELISA kit  from Biorbyt Ltd., Cambridge, UK. The detection range for the kit is between 125-8000 pg/mL. The mean minimum detectable dose (sensitivity) of the assay is 60 pg/mL. HMGB1 concentration was measured using an EIAB Human HMGB1/high mobility group protein B1 ELISA kit  from EIAB Science, Wuhan, China. The detection range for the kit is between 0.156-10.00 ng/mL. The mean minimum detectable dose (sensitivity) of the assay is 0.1 ng/mL.in vitro latex enhanced immunoturbidimetric method using a Cobas Integra 400 plus analyzer  from Roche Diagnostics, Penzberg, Germany, according to the manufacturer’s instructions. Plasma samples were not diluted before analysis. The manufacturer of the assay kit referred to the diagnostic repeatability coefficient of variation (CV%) as 3.4% at CRP mean concentration of 1.33 ± 0.0451 mg/L and diagnostic precision CV% as 4.4% at CRP mean concentration of 1.33 ± 0.0586 mg/L.CRP concentration was measured by the th and 75th percentiles. The data was tested for normality using the Shapiro-Wilk test. Because the tested parameters did not pass the normality test, results obtained in this experiment were analyzed by the Mann-Whitney U test or Wilcoxon matched pairs test (two-sided nature). The differences in continuous variable values between the study and control groups were assessed using the Mann-Whitney U test. To compare paired data obtained 30 min. before and 12-14 hours after closed reduction with Kirshner wire fixation in children with a distal forearm fracture, the Wilcoxon matched-pairs test was used. Correlations were studied by using Spearman’s Correlation test. Differences were considered significant with a value of p<0.05.Statistical analysis was performed using the STATISTICA PL release 12.5 Program. All the results are presented as median with 25The sample size was calculated with an independent two-sided t-test by choosing a 95% confidence level, a margin of error of ± 5%, power of 80%, the size of the pediatric population in our region, and the number of cases performed per year.The concentration of the analyzed cytokines, except for IL-33, and DAMPs was within the range of the assay kit in all plasma samples of children with a distal forearm fracture.HSP-70 concentration measured 30 min. before the CRKF procedure was statistically higher in comparison to the control group. In contrast, we did not observe significant changes in HMGB-1 concentration as a consequence of distal forearm fracture. HMGB-1 and HSP-70 concentrations measured 12-14 hours after the CRKF procedure did not significantly differ as compared to the control group Table 2.HMGB-1 and HSP-70 concentrations 12-14 hours after the CRKF procedure was performed were lower than those measured 30 min. before the CRKF procedure, but the obtained differences were not significant Table 2.IL-33 concentration in all plasma samples taken from children with a distal forearm fracture 30 min. before the CRKF procedure, 12-14 hours after the CRKF procedure, and from the control group were below the detection limit of the assay kit.CXCL5 concentration measured 30 min. before the CRKF procedure and measured 12-14 hours after the CRKF procedure was lower than the concentration obtained from the control group, but the differences were not significant. Chemokine concentration also did not statistically differ between samples obtained from children 30 min. before the CRKF procedure compared to samples obtained 12-14 hours after the CRKF procedure Table 2.IL-8 concentration measured 30 min. before the CRKF procedure and measured 12-14 hours after the CRKF procedure was almost the same as the concentration obtained in the control group. Moreover, IL-8 concentration did not differ between samples obtained from children 30 min. before the CRKF procedure compared to samples obtained 12-14 hours after it Table 2.IL-6 concentration measured 30 min. before the CRKF procedure was significantly higher than in the control group. The increase was 4.3-fold. Additionally, IL-6 concentration measured 12-14 hours after the CRKF procedure was significantly higher as compared to the control group. IL-6 concentration evaluated in samples obtained 12-14 hours after the CRKF procedure was also significantly higher as compared to samples obtained 30 min. before the CRKF procedure Table 2.CRP concentration measured 30 min. before the CRKF procedure was significantly higher than in the control group. CRP concentration measured 12-14 hours after the CRKF procedure was also significantly higher as compared to the control group. Additionally, CRP concentration evaluated in samples obtained 12-14 hours after the CRKF procedure was significantly higher as compared to samples obtained 30 min. before the CRKF procedure Table 2.s), which play a role in post-fracture inflammation and fracture healing. It was further confirmed by Baht et al.  concentration, as they promote tissue repair and resolution of the inflammation. The release of DAMPs is a highly relevant mechanism by which immune cells can be alerted to tissue damage . TanigucWe showed that HMGB-1 concentration did not change in response to the distal forearm fracture in children. The lack of a significant difference in comparison to the control group may indicate that this kind of injury is not as severe as traumas presented by other authors , 23. It In contrast to HMGB-1 concentration, we observed significant growth of plasma HSP-70 concentration in children with distal forearm fracture compared to the control group. It may indicate that among DAMPs HSP-70 responds earlier to bone injury in comparison to HMGB-1. It is evidenced that HSPs play important roles in situations involving both systemic and cellular stress . GiffardResults concerning the kinetics of HMGB-1 and HSP-70 in the plasma of children after closed reduction with K-wire fixation raise some points of interest. We observed, that concentrations of both DAMPs decreased 12-14 hours after the CRKF procedure. In this context, it is interesting to record that Cohen et al.  postulatCRP concentration may reflect the development and augmentation of an inflammatory response, as we showed in several of our previous studies , 31–33. Several studies demonstrated that IL-33 is passively released after tissues damage, which may suggest that this alarmin cytokine alerts the immune system after endothelial or epithelial cell damage during infection, physical stress, or trauma , 35. TheOne of the study limitations could be the fact, that in our children population, only two patients from twenty-nine had a hospitalization time lasting 2 days. Moreover, none of the patients had intraoperative/postoperative complications. Nevertheless, it would be interesting to evaluate how selected inflammatory cytokines , CRP, and damage-associated molecular patterns  are related to fracture healing, tissue repair, and outcome . However, such an experiment requires selecting and collecting a new group of children, having longer than usual time of hospitalization, and with reported intraoperative/postoperative complications. It would be also interesting to evaluate the concentrations of other inflammatory cytokines, including IL-1β and TNF-α. Conducting these analyzes would be impossible with the current experiment because it would require more amount of plasma. This also could be recognized as a study limitation. Another study limitation is a small sample size. Thus it needs to emphasize, that this kind of study should be interpreted carefully. However, data acquired from such experiments could be used to design larger confirmatory analyses to provide final conclusions.To conclude, increased values of IL-6, CRP, and HSP-70 represented an early inflammatory response to distal forearm fractures classified as SH-II type according to the Salter-Harris classification system. However, the median CRP concentration was within the reference values not indicative of the inflammatory state. The CRKF procedure may be a good solution for the treatment of bone fractures, as damaged associated molecular patterns – HMGB-1 and HSP-70 – did not significantly differ 12-14 hours after the approach was applied as compared to the control group. Moreover, the growth of IL-6 concentration after the CRKF procedure was 1.5-fold to the level before CRKF, while the increase of this marker in response to the distal forearm fracture was 4.3-fold compared with the control group. Based on this data, it appears reasonable to suggest that the CRKF approach caused less damage and inflammatory response in comparison to the response to the fracture. Nevertheless, further research should be conducted to evaluate how the immunomodulation of selected cytokines and DAMPs may have a therapeutic potential to hasten and improve bone healing.The datasets generated and analyzed during the current study are not publicly available but all are kept at the Medical University of Bialystok and are available from the corresponding author on reasonable request.Approval for this study was obtained from the Bioethics Committee of the Medical University of Białystok (No: R-I-002/45/2018). Procedures were following the ethical standards set out in the Declaration of Helsinki put out by World Medical Association. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.MT: conception and design of the study, acquisition of data, analysis and interpretation of data; visualization, drafting of the article. TG: acquisition of data, revising article for its content. MM: acquisition of data, revising article for its content. JK: methodology, revising article for its content. EM: acquisition of data; revising article for its content. MK: acquisition of data; revising the article for its content. OK-L: conception and design of the study, methodology, analysis, and interpretation of data; visualization; resources; drafting of the article. All authors contributed to the article and approved the submitted version.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Lycium barbarum polysaccharide (LBP) is the main bioactive component of Lycium barbarum, which has a protective effect on male reproduction, but its mechanism is still unclear. In this study, our results proved that LBP blocked the inhibitory effect on the proliferation activity of Sertoli cells after heat stress, reversed the dedifferentiation of Sertoli cells induced by heat stress, and ameliorated the structural integrity of the blood-testis barrier. In addition, it increased the expression of the androgen receptor and activated Akt signaling pathway to resist heat-stress-induced injury of Sertoli cells.Male infertility induced by heat stress has been attracting more and more attention. Heat stress not only causes apoptosis of spermatocytes but also has adverse effects on Sertoli cells, further damaging spermatogenesis.  More than half of the childbearing couples could not have children due to male infertility , 2, whicSpermatogenesis depends on mature Sertoli cells (SCs). In the seminiferous tubule, SCs provide structural support and supply nutrients, functional proteins, and cytokines for spermatogenesis , 14. TheAndrogen receptor (AR) is a type I steroid receptor. Androgens have to bind to AR before they can regulate the development of germ cells and SCs. Expressed in SCs, an androgen receptor (AR) plays a crucial role in spermatogenesis , 21. StuLycium barbarum polysaccharide , the main component of Chinese wolfberry, is characterized by high bioactivity and significant content [ content . The glu content . Evidenc content –32. HoweLycium barbarum polysaccharide powder was purchased from Nanjing Manhay Medical Technology .DMEM/F12, 0.25% trypsin-ethylenediaminetetraacetic acid, collagenase IV, fetal bovine serum (FBS), and penicillin-streptomycin liquid were purchased from Gibco . 3--2,5-diphenyltetrazolium bromide (MTT), dimethyl sulfoxide (DMSO), phosphate buffered saline (PBS), and the bicinchoninic acid (BCA) protein assay kit were purchased from Solarbio Life Sciences . SP link detection kits (biotin-streptavidin HRP detection systems) and the diaminobenzidine kit were purchased from ZSGB-BIO . The anti-Ki67 (ab16667) and anti-AR (ab133273) were purchased from Abcam . The anti-occludin (PA5-20755) and anti-zonula occludens-1 (61-7300) were obtained from Thermo Fisher Scientific . The anti-Phospho-Akt (Ser473) (#4060) and anti-Akt (#4691) were obtained from Cell Signaling Technology . The anti-CK-18 antibody (10830-1-AP) and anti-beta-actin antibody (60008-1-lg) were obtained from Proteintech .Mature male Sprague Dawley rats (8 weeks of age) were purchased from Huafukang . These rats were treated and sacrificed according to the National Institutes of Health Guidelines for the Care and Use of Laboratory Animals . All animal procedures were approved by the Laboratory Animal Welfare and Ethics Committee of the Beijing University of Chinese Medicine (BUCM-4-2017010805-010).2 incubator (5% CO2/95% air). After 40 h culturing, the medium was replaced to remove unattached germ cells, and 12–24 h later, when cells were confluent, they were ready for the following experiments. LBP was dissolved and diluted with PBS into different concentrations and then was added in SCs at the dose of 25 mg/L, 50 mg/L, and 100 mg/L. Cells in the control group and heat-stress group were added with the same volume of PBS. After 24 h, the control group was cultured at 35°C for another 20 minutes, and the other groups were treated in a 43°C water bath for 20 minutes.Sertoli cell isolation was according to the previous method . BrieflyMTT assay has been widely used for measuring cell viability. The obtained absorbance value  under the specific wavelength is directly proportional to the number of living cells. SCs were seeded at 5 × 104 per well in 96-well plates in DMEM/F12 supplemented with 10% FBS. Cells were treated with LBP in different concentrations or PBS for 24 h. After removing some supernatant, an MTT regent (5 mg/ml) was added to each well for four hours. Then SCs were treated with DMSO by shaking for 15 min at room temperature, and the OD value was measured at 570 nm by using a microplate reader FLUO Star Omega . The blank group had no cells in wells and was used as the zero point of absorbance. Also, the absorbance value of each group divided by the control group was cell viability (%).The immunohistochemistry protocol in our experiment followed that described previously . SCs werβ-Actin (1 : 5000) was used as an internal control for AR, CK-18, occluding, and zonula occludens-1. Akt was used as an internal control for phosphorylated-Akt in Ser473. Band intensities were determined by the software Quantity One, Version 4.6.2 .Western blot was performed as described previously , 36. TheP < 0.05 was considered as significant, and P < 0.01 was considered as highly significant.Each experiment was repeated at least three times. Statistical analysis was performed with the software SPSS version 20.0 . Data that conformed to normal distribution or approximate normal distribution are expressed as means ± standard error of the mean (SEM). One-way analysis of variance was used for analyzing the data in different groups, and the pairwise comparisons were tested by the Tukey multiple comparison test. P < 0.05 or P < 0.01), while the differences in other LBP groups were not statistically significant (P > 0.05). Therefore, these three concentrations were selected as the concentration of LBP drug groups.To observe the effect of LPB on cell viability and select appropriate drug concentrations, we detected the OD value by MTT. As shown in P < 0.05 or P < 0.01), and the 50 mg/L LBP and 100 mg/L LBP group have no significant change. Compared with the heat-stress group, the positive signal of Ki67 in LBP treatment groups showed a noticeable increase (P < 0.01). These data indicated that LBP treatment could resist the reduction of Ki67 expression induced by heat stress; however, the 25 mg/L LBP group still had a noticeable difference compared to the control group, and 50 mg/L LBP and 100 mg/L LBP could improve the proliferation activity of SCs after heat stress to the level of normal statement.To investigate the effect of LBP on the proliferation activity of SCs after heat stress, we tested the Ki67 in SCs . Ki67 exP < 0.05 or P < 0.01) when compared with the control group. Moreover, compared with the heat-stress group, the expression of CK-18 in LBP treatment groups  decreased significantly (P < 0.01).To observe the effect of LBP on the differentiation of SCs, we tested the expression of CK-18 . The expP < 0.05 or P < 0.01). Compared with the heat-stress group, the expression of occludin and zonula occludens-1 in LBP treatment groups increased significantly (P < 0.01) in a dose-dependent manner (P < 0.05 or P < 0.01).To clarify the effect of LBP on BTB, we detected the TJ-associated protein, occludin  and zonuP < 0.01) after heat treatment. Compared with the heat-stress group, the expression of AR in LBP treatment groups increased significantly (P < 0.01).Testosterone only works when combining to the androgen receptor. To determine the AR in SCs and to better understand the mechanism of AR, we analyzed AR with immunohistochemistry staining  and westP < 0.01). Compared with the heat-stress group, the expression of p-Akt (Ser473) in LBP treatment groups increased significantly (P < 0.01). These data indicated that Akt phosphorylation at Ser473 was involved in the protective effect of LBP on SCs and BTB.We all know the critical role of the Akt signaling pathway in cell activity. It has been found that there is an interaction between AR and Akt phosphorylation at Ser473 . ConsequSertoli cells are the most crucial somatic cells for spermatogenesis. The number and maturations of SCs determine the spermatogenesis. In this study, our data indicate that LBP could resist the decrease of proliferation activity, inhibit the dedifferentiation of SCs after heat stress, and more importantly, preserve BTB integrity and permeability by maintaining AR and phosphorylated-Akt (Ser473).L. barbarum fruits [Lycium barbarum fruits, as a traditional Chinese medicine and health food for people, have been used to nourish the kidney and improve fertility for thousands of years , 39. Them fruits . Also, Lm fruits . RecentlTemperature is an essential controller for reproductive activity and testicular homeostasis . Only caWe first selected three suitable concentrations of LBP by MTT  to treatThe formation of BTB occurs at the beginning of puberty, and BTB is partly composed of tight junction (TJ), which directly affects the permeability . OccludiIt is well known that testosterone and AR are the decisive factors for maintaining male fertility and secondary sexual characteristics. AR is believed as a crucial upstream factor in controlling the development of SCs and the forming of BTB . AR defiAkt/protein kinase B (PKB), a serine/threonine kinase, is a mediator in the growth and proliferation of Sertoli cells , 67. AktIn summary, our study indicates that LBP can preserve the expression of Ki67 and occludin and zonula occludens-1 and inhibit the expression of CK-18 to prevent heat-stress-induced impairment of Sertoli cells and BTB through maintaining AR and Akt phosphorylation at Ser473 . Also, i


To evaluate the efficacy and safety of transarterial chemoembolization (TACE) combined with camrelizumab  in the treatment of patients with recurrent hepatocellular carcinoma (R-HCC) after curative resection.R-HCC patients who underwent TACE plus camrelizumab or TACE-alone from January 2016 to August 2021 were retrospectively evaluated. Patients were assessed for tumor response, progression-free survival, survival rates and adverse events.P = 0.201). The disease control rates were 84.3% in TACE-alone group and 80% in TACE-camrelizumab group at 3 months (P = 0.663). The progression-free survival (PFS) of the TACE-alone group was slightly longer than those of the TACE- camrelizumab group (9 months vs. 6 months). However, there were no statistically significant differences in the median PFS (P = 0.586). Similarly, there were no significant differences in the half-year and one-year survival rates . Multivariate analysis revealed that Neutrophil-to-lymphocyte ratio (NLR) was associated with PFS significantly. 75% patients developed at least one type of AEs related to camrelizumab in TACE-camrelizumab group, and no patients developed severe AEs.Seventy-one patients were included in this study, including 20 patients in the TACE- camrelizumab group and 51 patients in the TACE-alone group. The objective response rate was 56.9% in the TACE-alone group and 40% in the TACE-camrelizumab group at 3 months (Comparing with TACE-Alone, the efficacy of TACE-camrelizumab for patients with R-HCC was similar. Meanwhile, the results of this study also indicated that TACE is still a better choice for patients with R-HCC. Hepatocellular carcinoma (HCC) is the fifth most common carcinoma and the second leading cause of cancer-related death . AlthougCompared to surgical resection, transarterial chemoembolization (TACE), which combines targeted chemotherapy with ischemic necrosis caused by arterial embolization, is a well-tolerated procedure with limited liver toxicity and can be employed for any type of HCC , 7. TherIn recent years, anti-PD-1 antibodies, including nivolumab, pembrolizumab, and camrelizumab, have demonstrated promising anti-tumor effects as monotherapy for HCC –16. One However, as far as we know, no studies have been reported on TACE combined with camrelizumab in R-HCC patients. Therefore, the objective of this study was to assess the efficacy and safety of TACE-camrelizumab verse TACE-alone in R-HCC patients.We reviewed the medical records of patients with recurrent HCC after curative resection who received treatment with TACE-camrelizumab or TACE-alone between January 2016 and August 2021 at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. This retrospective study was approved by the institutional review board of the Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Written informed consent for the patients’ data to be used for research purposes was obtained from all patients prior to treatment.All of the patients included in this study met the inclusion criteria: 1) Adult patients whose diagnosis of HCC depended on the guidelines of the European Association for the Study of Liver and the American Association for the Study of Liver Disease [ Adult paTACE was performed by placing a 5-F catheter  or a 2.7-F microcatheter  into hepatic tumor feeding arteries. Initially, an emulsion of 2–20 mL lipiodol and 20–60 mg epirubicin was administered into the target vessels under fluoroscopic guidance. Next, gelatin sponge particles  were administered into the tumor donor arteries. Embolization was operated under fluoroscopic guidance until the stasis of arteries flow was occurred. Finally, reexamination angiography of the hepatic artery was performed to validate the devascularization.Patients were treated with camrelizumab within 2–3 weeks after TACE procedure. Camrelizumab was administered intravenously at a dose of 200 mg every 3 weeks. When serious adverse events (AEs) emerged, we reduced the dosage of drugs or interrupted it and symptomatic treatment such as glucocorticoids or immunosuppressant agents were administered, depending on the severity and the affected organs.All patients were followed up until 31 July 2021. Patients were evaluated every 6–8 weeks with laboratory and abdominal contrast-enhanced CT or MR. Tumor response was evaluated based on Response Evaluation Criteria in Solid Tumors (RECIST 1.1) and Modified RECIST (mRECIST) . HoweverThe primary endpoint was progress-free survival (PFS). The secondary endpoints were ORR and DCR. PFS was defined as the period between the date of the initial TACE after being diagnosed with R-HCC and the date of the diagnosis of tumor progression or patient death. The ORR was defined as the percentage of patients with a complete response (CR) or partial response (PR). DCR was defined as the percentage of patients with CR, PR or stable disease (SD). Adverse events attributed to TACE or camrelizumab treatment were recorded and assessed by The Common Terminology Criteria for Adverse Events Version 5.0. In addition, postembolization syndrome, such as fever, pain, nausea and vomiting, is not considered an AE in itself, but rather an expected outcome of embolization therapy .P value less than 0.10 in univariate analysis were added to multivariate analysis. P < 0.05 indicated a statistically significance.All analyses were performed by using SPSS software, Version 24.0 . Discrete variables were represented by numbers with percentages and were calculated by Chi-square test, and continuous variables were presented as mean ± standard deviation and were calculated by Student’s t-test. Kaplan–Meier method and log-rank test were performed to evaluate the differences in PFS and survival rates between the two groups. The 95% confidence interval (CI) was calculated for median PFS and hazard ratio (HR). Log-rank test was used for univariate analysis, in which variables with A total of 353 R-HCC patients underwent a treatment of either TACE- camrelizumab or TACE-alone in the study. 282 patients were excluded from the study and 71 patients were finally included in this analysis: 20 patients were treated with TACE-camrelizumab and 51 patients were treated with TACE-alone  and disease control rate (P = 0.663) between the two groups.The response of the tumor was determined by the abdominal contrast-enhanced CT or MR imaging. In the TACE–camrelizumab group, 1 patient (5%) achieved complete response, 7 patients (35%) achieved partial response, and 8 patients (40%) achieved stable disease. Therefore, the objective response rate and disease control rate were 40% and 80%, respectively. In the TACE–alone group, 18 patients (35.3%) achieved complete response, 11 patients (21.6%) achieved PR, and 14 patients (27.5%) achieved SD. Therefore, the objective response rate and disease control rate were 56.9% and 84.3%, respectively. The chi-square test indicated that there was no significant difference in objective response rate (P = 0.586)  . The one-year survival rate was estimated at 60.7% and 49.0% in the TACE–camrelizumab group and TACE–alone group, respectively (P = 0.430). In the patients at the stage of BCLC-C, the half-year survival rate was 94.4% in the TACE-camrelizumab group, and 83.8% in the TACE-alone group with no significant difference (P = 0.264). The one-year survival rate was 65.0% in the TACE- camrelizumab group, and 40.5% in the TACE–alone group with no significant difference (P = 0.177).The median PFS was 6 months  in the TACE- camrelizumab group, and 9 months  in the TACE-alone groups. No statistically significant difference was found between the two groups in the median PFS (86) Fig. A. In theIn the TACE-camrelizumab group, 9 patients (45%) developed fever (n = 7), abdominal pain (n = 4), nausea and vomiting (n = 4) within one week after TACE, and in the TACE-alone group, 16 patients (31.4%) developed fever (n = 11), abdominal pain (n = 8), nausea and vomiting (n = 6) within one week after TACE. After symptomatic treatment during hospitalization, the symptoms of all patients were alleviated or eliminated.AEs related to camrelizumab are shown in Table Because of the high risk of tumor recurrence after liver resection, it is urgent to find an effective treatment for the recurrence that can be used repeatedly and is suitable for patients with limited reserve of liver function. TACE is usually used in this kind of patients, but TACE alone cannot replace repeated liver resection. However, TACE increases tumor-specific CD8 + T cell response and programmed death receptor 1 (PD-1) and programmed death ligand 1 (PD-L1) expression, which provides an impetus for the exploration of immunotherapy after TACE . In thisP = 0.006). Besides the new criteria for progression, another possible factor of the positive results was that sorafenib was given 2–3 weeks before initial TACE was performed [The median PFS in patients treated with TACE alone was 9 months , longer than 6 months reported for TACE-camrelizumab. According to the previous research and our hypothesis, the addition of ICIs was helpful for patients who underwent TACE treatment in patients with primary HCC , but ourerformed . In thisSome studies demonstrated the efficacy of transarterial embolization combined with ICIs in the treatment of primary HCC , 34. HowIn the TACE-camrelizumab group, 70% of patients developed at least one type of AEs after treatment with camrelizumab, and all of the AEs were grade 1 or 2. These AEs were significantly improved after symptomatic treatment. Similar to the previous study, reactive cutaneous capillary endothelial proliferation (RCCEP) is the most common adverse event related to the camrelizumab, but RCCEPs were clinically controllable and self-limiting . OverallOur study had limitations. First, our study was retrospective, and the sample size in the two treatment groups was relatively small, therefore, it was difficult to make strong conclusions about these results. Second, our study was conducted in a single center. Finally, due to the relatively short period of follow-up time, this study did not achieve median OS. Therefore, it is necessary that prospective multicenter clinical trials be conducted in the future to validate our findings.In summary, this study is the first one to report the efficacy and safety of the TACE combined with camrelizumab in the treatment of R-HCC patients, and the results indicated that this combination therapy had a similar effect on R-HCC patients compared with TACE-alone, which reminded us that TACE was still a better choice for patients with R-HCC. At the same time, the treatment of TACE combined with camrelizumab had an acceptable safety profile, with no occurrence of severe AEs. Although this study did not demonstrate the superiority of TACE-camrelizumab over TACE-Alone, the results can definitely serve as an important reference for other research.